Target detecting and tracking are two of the core tasks in the field of visual surveillance. The tracking aims to achieve precise positioning of a target in video successive frames to derive a target trajectory, which has extremely high application value in practical oriented airborne-based monitoring scenarios.
In traditional visual monitoring methods, the monitoring data is often captured by using a horizontal visual angle or a low visual angle camera that is fixedly arranged. With the rapid development of Unmanned Aerial Vehicle (UAV) technology in recent years, the monitoring based on data from drone-mounted airborne-based camera is growing in popularity and importance. Such airborne-based monitoring data has the advantages of higher visual angle, less concealment, larger coverage area, quick and flexible deployment and low maintenance cost, etc. At the same time, however, many challenges have been raised for target tracking methods based on such surveillance video.
However, the high visual angle of the monitoring data based on the drone-mounted airborne-based camera data tends to result in a small target dimension and insufficient appearance information. Additionally, the flexible and maneuverable deployment of the airborne-based platform leads to variable and unpredictable types of targets that may occur in the monitoring scenarios. Moreover, the mobility of the airborne-based platform can enable the captured surveillance video to contain a certain lens motions, thereby affecting the reliability of the target motion features in the video.